Effectiveness of Differential Privacy and L2 Regularisation Against Membership Inference Attacks in Deep Learning
It is demonstrated that L2 regularization provides comparable defence against membership inference attacks as DP-SGD, particularly for larger datasets, and that L2 regulation achieves precision, recall, and accuracy values within 2-4% of those achieved by DP-SGD across all experimental conditions.